A few key differences. Restate has a more flexible programming model. You don't write workflows with activitities, but just durable processes/handlers. Durable steps execute inline and get persisted over an open streaming connection in Restate (low latency, lower overhead per durable step, sharing resources like sandboxes) instead of working with a pull-model where each activity executes remotely on a worker. Restate has a lean deployment model with a single binary that can be deployed multiple times to have a highly-available cluster (potentially spread across multiple regions). It is used for large-scale production clusters, and so lightweight here does not mean less reliable than Temporal.
You can do the same things with Temporal like sleep for months etc. You can learn more here: https://restate.dev/vs/temporal
* local: executed in the same process as the orchestrator code. Many local activities can be executed locally before their results are sent to a backend server in a single RPC call.
* task queue based: executed by a pool of worker processes that poll from the queue. This is the most flexible model as it supports flow control, priorities, fair queueing out of the box.
* eager dispatch: task queue based but executed locally if possible as a performance optimization.
Temporal also supports stand alone activities that are invoked without a workflow and dispatched through a task queue.
Restate only supports local activities (using Temporal terminology).
I wouldn't call it a "more flexible programming model".
Restate made several decisions I consider questionable for the system's availability and stability, like pushing work to handlers instead of dispatching it through a queue. Any design decision has tradeoffs. It would be nice if you mentioned these trade-offs in your posts instead of making claims that sound like pure marketing.
Sorry, but this is incorrect (Restate founder here)
(1) You can model the equivalent of local activities and activities that run on other workers in Restate.
A local activity is a step in the workflow function. An activity supposed to run on a different worker is a function called by the workflow function. Since these calls are just Restate events, exactly-one, suspendable, this gives you a full-fledged workflow/remote-activity pattern. Including concurrency, separate retry policies, etc.
(2) Restate steps commit individually, unlike local activities.
Imagine a two-step workflow, where you want one step durable before starting the second. Account withdrawal before deposit. Restate steps allow you to do that, each step is durable committed before the next step runs.
Per Temporal's own docs, Temporal Local Activity results become durable only when the enclosing Workflow Task completes. That's different than Restate, which can durably commit every individual ctx.run before proceeding to the next step.
Making actual durable commits fast, so you can have sequences of fast durable steps building on each other is super valuable. If an agent can commit the guardrail evaluation in low milliseconds before it starts the tool call, that's great, do it. If committing this involves dispatching another workflow or activity task, the consideration is harder.
When we see someone migrate a Temporal workflow, they often end up using many more durable steps in Restate than they used activities before.
(3) Why do we consider it flexible?
(a) Virtual Objects: Keep state around across the workflow, without doing tricks like "keep the workflow running, signal only, continue_as_new" after a while. Virtual Objects are a natural way to model concurrent stateful entities.
(b) non-workflow communication patterns: We have seen users build lot's of different patterns. It can get as crazy as graphs of functions/objects sending each other durable messages. All end-to-end idempotent (or exactly once, for Virtual Object state). That is outside the hierarchical workflow/subworkflow/activity abstraction.
(4) availability and stability
I don't know where the perception with stability comes from, Restate pushes some pretty high volumes for customers, like 100k+ actions/sec.
The push model in Restate is internally dispatched through queues as well. The application just don't see it as task queues. Limits are implemented through virtual-queues in Restate 1.7.
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Of course the systems make different trade-offs. The Restate design (vqueues, push model) is took us longer to build than a task queue model would have, because it puts more work onto the dispatcher that is otherwise handled just implicitly by the worker pools.
But once it is there, it is sooo nice, in how easy it integrates into infra, and how it can handle flow-control with high hierarchical limits in ways I genuinely haven't seen in any other system achieve (see https://restate.dev/blog/announcing-restate-1-7 )
Might not be par for the course for HN, but gotta drop a link with a light joke, with the background of the money grubbing guy (Temporal founder here) sucking up venture capital like vacuum cleaner who tries to argue he’s intellectually superior in a brag thread about his Company over a competitor (with significant OSS accomplishments) who is attempting to make the world a better place with a freely available primitive that isn’t just available to dev teams at mega teams at Netflix and OpenAI etc.
Hmmm, that feels not very nice, tbh. I have big respect for what Maxim and the team built, and both systems are essentially open and free (publish code and are free to use).
Do you realize that Temporal is fully open source under the MIT License, while the competitor is under BSL?
I certainly don't think I'm superior to them in any way and have great respect for the very capable team they are. We know each other personally. I even presented at the Flink conference while at Uber.
My message is that I'd prefer a more technical discussion of the merits of our products rather than simplified marketing attacks.
How does that compare to Inngest? As I understand it it also executes inline and has a streaming connection to the inngest server. We ended up going with them over temporal because it was so much simpler operationally, but restate seems even lighter. I can appreciate how it's hard to tackle the enterprise market, but the temporal solution feels so bloated I really hope the industry can standardize on some simpler patterns
The way it works is that Restate supports suspending workflows that sleep for months and later (once the sleep finishes) resumes them at exactly this point. Technically, this is the same process as resuming a crashed workflow.
While the workflow is actively doing work (like calling other services, accessing state or interacting with external services, for example) the server is connected to the workflow deployment via a low-latency bidirectional streaming connection to receive and acknowledge progress that the workflow makes. That way the workflow can finish as fast as possible.
A nice side effect of this model is that you can co-locate your workflow with expensive resources, such as a sandbox, which should be used by all durable actions that the workflow executes. The reason this works is because Restate can inline durable steps (what would be modeled in Temporal as activities, I believe).
If a handler starts a sleep/human approval/RPC call, or so, then this timer/promise is persisted in Restate's journal. Restate does the waiting. The handler process itself can suspend (e.g. on a serverless function), and the bidirectional connection is closed. Once the timer fires/approval comes in, Restate re-invokes the service with the journal of previously completed steps, and the service can replay to the exact point in the code where it suspended and continue from there. Restate is like a DB for journals, so you can sleep for as long as needed, also months.
So you have fast persistence of events while a handler can make progress, and suspensions while waiting.
I guess the confusion is that it doesn't have to be one single persistent stream.
While the durable function does fast work and adds steps, it pushes it through a stream. When a wait point comes, it closes and replays on resumption (typical durable execution style).
That gives you the best of both worlds: same long-running workflows with long sleets and suspensions, but also ability to add steps with few ms overhead only.
As agents run longer and spend more money, many agent frameworks are adding resiliency features like checkpoint recovery and pause-resume approvals.
But to get your agent to production, checkpointing is not enough. There is quite a big gap left for you to handle: failure detection, automatic retries, high availability, scale-out, idempotency, concurrency, session coordination, versioning, ...
I wrote a blog post on what’s left to solve, and how to solve it.
TL;DR Instead of tying resiliency together with your agent framework, agents should be built on top of a highly-available orchestration layer that owns the end-to-end execution, guarantees it completes, and handles all of the points above.
Optionally, agent frameworks can be used on top of this to help abstracting away the agent loop.
Is this also how you see it and productionize your agents?
AI agents often run for minutes, hours, or even days. This makes deploying new versions tricky: what happens if an agent starts on one version of your code and resumes later after you’ve deployed another?
If you swap out code from under an agent, execution can break. Or worse, a changed description or tool implementation can cause your agent to silently misinterpret its own history and produce inconsistent results.
This blog post introduces how to solve this via immutable deployments and pinned executions:
- Each deployment lives at a unique endpoint and represents an immutable, versioned snapshot of your code, prompts, tools, and schemas
- Every execution is pinned to its deployment; retries, resumptions, and callbacks always return to the same version
- New requests route to latest
The blog post shows how Restate implements this in practice. Versioning becomes an infrastructure property you don’t need to think about, rather than something you solve in code.
Here is a fan-out example for async tasks: https://docs.restate.dev/use-cases/async-tasks#parallelizing...
First, a number of tasks are scheduled, and then their results are collected (fan-in). This probably comes closest to what you are looking for.
Each of those tasks gets executed durably, and their execution tracked by Restate.
A few key differences. Restate has a more flexible programming model. You don't write workflows with activitities, but just durable processes/handlers. Durable steps execute inline and get persisted over an open streaming connection in Restate (low latency, lower overhead per durable step, sharing resources like sandboxes) instead of working with a pull-model where each activity executes remotely on a worker. Restate has a lean deployment model with a single binary that can be deployed multiple times to have a highly-available cluster (potentially spread across multiple regions). It is used for large-scale production clusters, and so lightweight here does not mean less reliable than Temporal.
You can do the same things with Temporal like sleep for months etc. You can learn more here: https://restate.dev/vs/temporal